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使用柔顺、连续关节四足机器人进行复杂地形穿越的设计优化

Design Optimization for Rough Terrain Traversal Using a Compliant, Continuum-Joint, Quadruped Robot.

作者信息

Sherrod Vallan, Johnson Curtis C, Killpack Marc D

机构信息

Robotics and Dynamics Laboratory, Department of Mechanical Engineering, Brigham Young University, Provo, UT, United States.

出版信息

Front Robot AI. 2022 Jul 11;9:860020. doi: 10.3389/frobt.2022.860020. eCollection 2022.

Abstract

Legged robots have the potential to cover terrain not accessible to wheel-based robots and vehicles. This makes them better suited to perform tasks such as search and rescue in real-world unstructured environments. In addition, pneumatically-actuated, compliant robots may be more suited than their rigid counterparts to real-world unstructured environments with humans where unintentional contact or impact may occur. In this work, we define design metrics for legged robots that evaluate their ability to traverse unstructured terrain, carry payloads, find stable footholds, and move in desired directions. These metrics are demonstrated and validated in a multi-objective design optimization of 10 variables for a 16 degree of freedom, pneumatically actuated, continuum joint quadruped. We also present and validate approximations to preserve numerical tractability for any similar high degree of freedom optimization problem. Finally, we show that the design trends uncovered by our optimization hold in two hardware experiments using robot legs with continuum joints that are built based on the optimization results.

摘要

有腿机器人有潜力覆盖轮式机器人和车辆无法到达的地形。这使得它们更适合在现实世界的非结构化环境中执行搜索和救援等任务。此外,气动驱动的柔顺机器人可能比刚性机器人更适合存在人类的现实世界非结构化环境,因为在这种环境中可能会发生无意的接触或碰撞。在这项工作中,我们为有腿机器人定义了设计指标,以评估它们穿越非结构化地形、携带 payload、找到稳定立足点以及沿期望方向移动的能力。这些指标在一个针对16自由度、气动驱动、连续关节四足机器人的10个变量的多目标设计优化中得到了展示和验证。我们还提出并验证了近似方法,以保持任何类似的高自由度优化问题的数值可处理性。最后,我们表明,通过我们的优化发现的设计趋势在两个硬件实验中得到了验证,这两个实验使用了基于优化结果构建的具有连续关节的机器人腿。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e70/9310103/5cbfa457d9b0/frobt-09-860020-g001.jpg

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